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Libros sobre el tema "Sensors fusion for localisation"

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Publicado: 25 de mayo de 2024

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1

Hucks, John A. Fusion of ground-based sensors for optimal tracking of military targets. Monterey, Calif: Naval Postgraduate School, 1989.

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2

G, Buser Rudolph, Warren Frank B, Society of Photo-optical Instrumentation Engineers. y University of Alabama in Huntsville. Center for Applied Optics., eds. Infrared sensors and sensor fusion: 19-21 May, 1987, Orlando, Florida. Bellingham, Wash., USA: SPIE--the International Society for Optical Engineering, 1987.

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3

Multi-sensor data fusion with MATLAB. Boca Raton: Taylor & Francis, 2010.

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4

Otmar, Loffeld, Centre national de la recherche scientifique (France) y Society of Photo-optical Instrumentation Engineers., eds. Vision systems--sensors, sensor systems, and components: 10-12 June 1996, Besançon, France. Bellingham, Wash: SPIE--the International Society for Optical Engineering, 1996.

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5

Networked multisensor decision and estimation fusion: Based on advanced mathematical methods. Boca Raton, FL: Taylor & Francis, 2012.

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6

Otmar, Loffeld, Society of Photo-optical Instrumentation Engineers., European Optical Society y Commission of the European Communities. Directorate-General for Science, Research, and Development., eds. Sensors, sensor systems, and sensor data processing: June 16-17 1997, Munich, FRG. Bellingham, Wash., USA: SPIE, 1997.

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7

Intelligent Sensors, Sensor Networks & Information Processing Conference (2nd 2005 Melbourne, Vic.). Proceedings of the 2005 Intelligent Sensors, Sensor Networks & Information Processing Conference: 5-8 December, 2005, Melbourne, Australia. [Piscataway, N.J.]: IEEE, 2006.

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8

Intelligent Sensors, Sensor Networks & Information Processing Conference (2nd 2005 Melbourne, Vic.). Proceedings of the 2005 Intelligent Sensors, Sensor Networks & Information Processing Conference: 5-8 December, 2005, Melbourne, Australia. [Piscataway, N.J.]: IEEE, 2006.

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9

IEEE/AESS Dayton Chapter Symposium (15th 1998 Fairborn, OH). Sensing the world: Analog sensors & systems across the spectrum : the 15th Annual AESS/IEEE Dayton Section Symposium, Fairborn, OH, 14-15 May 1998. Piscataway, N.J: Institute of Electrical and Electronics Engineers, 1998.

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10

Green, Milford B. Mergers and acquisitions: Geographical and spatial perspectives. London: Routledge, 1990.

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11

Distributed sensor networks. 2a ed. Boca Raton: Chapman and Hall/CRC, 2013.

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12

Iniewski, Krzysztof y Kevin Yallup. Technologies for Smart Sensors and Sensor Fusion. Taylor & Francis Group, 2017.

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13

Iniewski, Krzysztof y Kevin Yallup. Technologies for Smart Sensors and Sensor Fusion. Taylor & Francis Group, 2017.

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14

Technologies for Smart Sensors and Sensor Fusion. Taylor & Francis Group, 2014.

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15

Iniewski, Krzysztof y Kevin Yallup. Technologies for Smart Sensors and Sensor Fusion. Taylor & Francis Group, 2017.

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16

Iniewski, Krzysztof y Kevin Yallup. Technologies for Smart Sensors and Sensor Fusion. Taylor & Francis Group, 2017.

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17

Yallup, Kevin. Technologies for Smart Sensors and Sensor Fusion. Taylor & Francis Group, 2014.

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18

Iniewski, Krzysztof y Kevin Yallup. Technologies for Smart Sensors and Sensor Fusion. Taylor & Francis Group, 2017.

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19

Hall, David L., Martin E. Liggins y James Llinas. Multisensor Data Fusion, Second Edition: Micro and Nano-Scale Sensors (Multisensor Data Fusion). 2a ed. CRC, 2008.

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20

L, Hall David, Martin E. Liggins y James Llinas. Multisensor Data Fusion, Second Edition: Micro and Nano-Scale Sensors. Taylor & Francis Group, 2008.

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21

L, Hall David, James Llinas y David Hall. Handbook of Multisensor Data Fusion. Taylor & Francis Group, 2001.

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22

Distributed Data Fusion For Networkcentric Operations. CRC Press, 2012.

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23

Llinas, James, David Hall y Martin Liggins II. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition. Taylor & Francis Group, 2017.

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24

Llinas, James, David Hall y Martin Liggins II. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition. Taylor & Francis Group, 2017.

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25

Llinas, James, David Hall y Martin Liggins II. Handbook of Multisensor Data Fusion: Theory and Practice, Second Edition. Taylor & Francis Group, 2017.

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26

Labrador, Miguel A. y Oscar D. Lara Yejas. Human Activity Recognition: Using Wearable Sensors and Smartphones. Taylor & Francis Group, 2013.

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27

Labrador, Miguel A. Human Activity Recognition: Using Wearable Sensors and Smartphones. Taylor & Francis Group, 2013.

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28

Institute Of Electrical and Electronics Engineers y OH) AESS Dayton Chapter Symposium (15th : 1998 : Fairborn. 1998 15th Annaul Ieee/Aess Dayton Chapter Symposium Analog Sensors and Systems Across the Spectrum. Institute of Electrical & Electronics Enginee, 1998.

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29

Panigrahi, Muktikanta y Arpan Kumar Nayak. Polyaniline based Composite for Gas Sensors. IOR PRESS, 2021. http://dx.doi.org/10.34256/ioriip212.

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In this research work, we have demonstrated the synthesis, spectroscopic characteristics, thermal behaviour and DC conductivity of a few nanostructured composites, substituted conducting polymers (ICPs) and composites of ICPs. The physical properties of aforementioned composites are significantly changed by the doping with HCl, H2SO4, HNO3, H3PO4, or acrylic acid. The charge transport properties of these polymeric materials have been studied in detail because of their potential application in gas sensors. In the current work, varieties of conducting polymer based materials such as PANI-ES/Cloisite 20A nanostructured composite, acrylic acid (AA) doped PANI polymer, N-substituted conducting polyaniline polymer, DL−PLA/PANI-ES composites, poly methyl methacrylate (PMMA) based polyaniline composite, and inorganic acid doped polyaniline are sucessfuly synthesized using aniline/aniline hydrochloride as precursors in acidic medium. Particularly, AA based synthesised PANI polymer was found with higher solubility The spectroscopic, thermal stability, enthalpy of fusion, room temperature DC conductivity and temperature dependent DC conductivity measurements with and without magnetic was carried out with as-synthesized materials. The FTR/ATR−FTIR spectra indicated the presence of different functional groups in the as-prepared composite materials. The UV−Visible absorption spectroscopic analysis showed the presence of polaron band suggesting PANI-ES form. The Room temperature DC conductivity, temperature variation DC conductivity (in presence and absence of magnetic field), and magnetoresistance (MR) of as-prepared conducting polyaniline based were analysed. The highest room temperature DC conductivity value was obtained from H2SO4 doped based composite materials and all prepared conductive composites were followed ohms law. The low temperature DC conductivity was carried out in order to study the semiconducting nature of prepared materials. The Mott type VRH model was found to be well fitted the conductivity data and described the density of states at the Fermi level which is constant in this temperature range. From MR plots, a negative MR was observed, which described the quantum interference effect on hopping conduction. We discuss different gas analytes i.e., NO2, LPG, H2, NH3, CH4, and CO of conducting polymer based materials.
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30

Sensing the world: Analog sensors & systems across the spectrum : The 15th Annual AESS/IEEE Dayton Section Symposium. Institute of Electrical and Electronics Engineers, 1998.

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31

GOVERNMENT, US. Proceedings of the 2005 Intelligent Sensors, Sensor Networks & Information Processing Conference: 5-8 December, 2005, Melbourne, Australia. Institute of Electrical & Electronics Enginee, 2006.

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32

(Editor), S. Sitharama Iyengar y Richard R. Brooks (Editor), eds. Distributed Sensor Networks (Chapman & Hall/Crc Computer and Information Science). Chapman & Hall/CRC, 2004.

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33

Brooks, R. R., N. K. Bose y S. S. Iyengar. Distributed Sensor Networks. Taylor & Francis Group, 2004.

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34

Cook, Diane J. y Narayanan C. Krishnan. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data. Wiley & Sons, Incorporated, John, 2015.

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35

Cook, Diane J. y Narayanan C. Krishnan. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data. Wiley & Sons, Incorporated, John, 2015.

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36

Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data. Wiley, 2015.

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37

Cook, Diane J. y Narayanan C. Krishnan. Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data. Wiley & Sons, Limited, John, 2015.

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38

Green, Milford B. Mergers and Acquisitions: Geographical and Spatial Persspectives. Taylor & Francis Group, 2012.

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39

Green, Milford B. Mergers and Acquisitions: Geographical and Spatial Persspectives. Taylor & Francis Group, 2011.

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